为什么 2 种方法计算 R2 分数的结果不同

如何解决为什么 2 种方法计算 R2 分数的结果不同

在线性模型中，SST（总平方和）= SSR（残差平方和）+ SSE（解释平方和），对吗？ 所以我用两种不同的方法计算了 R2 分数。

数据的形状是(n_sample,n_feature)，我想通过每个特征计算R2分数。

第一：R2 = SSE/SST

def r2score(y_pred,y_true):
    SSE = np.sum((y_pred - y_true.mean(axis=0)) ** 2,axis=0)
    SST = np.sum((y_true - y_true.mean(axis=0)) ** 2,axis=0)
    return SSE / SST

array([0.3903272,0.61556043,0.79316815,0.27477445,0.76132449,0.37335292,0.67222515,0.56178136,0.37840461,0.48753905,0.48425204,0.40274203,0.32436666,0.73934064,0.67582176,0.65503309,0.74719551,0.42158567,0.35102711,0.52308956,0.22078698,0.30651726,0.28614789,0.43199096])

第二：R2 = 1 - SSR/SST

def r2score_same(y_pred,y_true):
    SSR = np.sum((y_true - y_pred) ** 2,axis=0)
    return 1 - (SSR / SST)

array([0.43137207,0.58980204,0.75270556,0.31230454,0.80313592,0.2881272,0.68314465,0.61986317,0.36847796,0.456864,0.35585449,0.4385286,0.35472905,0.66386517,0.59598209,0.65243417,0.70413723,0.42801639,0.43712039,0.56682037,0.23902448,0.34432634,0.33884071,0.42886742])

我不明白为什么结果不一样。

请帮帮我！